Effect of unfunctionalized and HNO<sub>3</sub>‐functionalized MWCNT on the mechanical and electrical performances of PEMFC bipolar plates
Bibliographic record
Abstract
ABSTRACT This study aims at developing lightweight and high performance electrically conductive nanocomposites for proton exchange membrane fuel cell (PEMFC) bipolar plates (BPPs). These composites were made from an optimized co‐continuous mixture of Polyethylene terephthalate (PET) and polyvinylidene fluoride (PVDF) reinforced with highly conductive carbon additives composed of carbon black (CB) and synthetic graphite (GR). Multiwall carbon nanotubes (MWCNT) were functionalized then used to improve BPPs electrical conductivity and their mechanical properties, such as flexural and impact strengths. It was observed that the best BPP prototype was obtained using nitric acid (HNO3)‐functionalized MWCNT. The latter led to the smothest BPP surface, the lowest through‐plane resitivity (0.12 Ω cm) and the highest impact and flexural strengths. These results are attributed to the improved dispersion of the functionalized MWCNT, a result of their best compatibilization with the (PET/PVDF) polymeric phase. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 43624.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".